Modelling your process improvement initiative on another organization’s success is foolish—they are but a sample size of one!
A sample size of one success can also be due totally to luck. To guarantee your process improvement will be a complete certainty you must have repeated proof that what you copy will bring sure success to you too
We love great success stories: The wizard entrepreneur; the person who crusaded for a worthy cause; the champion athlete; the financial guru; the innovative business solution with astounding results; the failing firm that turned their fortunes around; the penniless emigrant whose wits made them wealthy. Those stories are inspirational. They challenge us to be better. They make us want to achieve more in our life roles and with our lives.
When you read books of such successes you get inspired and excited. Your enthusiasm rises, and you want to be a hero too. Go ahead and finish the book… but realize it describes a sample size of one. One example of a successful outcome is statistically irrelevant. One great result can easily be due totally to luck and nothing else. It is outstandingly foolish to accept one success as proof you can be successful at the same endeavour too.
As much as I love inspirational books—there have been many in my library over the years—I now realize that each was but one example. Each was a lone result—one person’s or one company’s success story. The business turn-around was at one site. The entrepreneur wrote about their one big success. The astounding business solution worked in one operation. The champion wrote of their personal story. The famous person told their life’s journey. Each is just a sample size of one. None of them is proof that what they did can ever be replicated again by anyone else.
Books and tales about people and companies that accomplished their dreams are not scientific evidence that the success can be replicated. Wonderful outcomes can also be the result of pure chance—like winning a chocolate wheel gift. So long as you have a ticket in the spin, when the chocolate wheel stops someone will win. Then the rest of us wonder why they were so fortunate, and how could we get the same?
The Scientific Method Never Accepts a Sample Size of One
In the scientific and research worlds, a sample size of one is distrusted. A single significant result is insufficient proof to act on—the great success could have been a random outcome. The second success could also be random luck. As too can be the third success, and even the fourth and fifth. In science and research, a result must be replicated in the same way several times sequentially by independent others to have confidence that a success was not only from a lucky event, or unintended, fortuitous misadventures.
Yet, in the business world, a sample size of one is enough reason to immediately make any change that looks good, from a great global-wide corporate reorganization, to a small a production process change. False assumptions and unknowns be damned!
I congratulate the hero and the guru, I celebrate their story, I buy their books, but if their success cannot be replicated by me in a trial using the same methodology and techniques as they advise, I take their book off my shelf.
I’m simply using the scientific method in my life and on my business to remove the element of luck and get true certainty.
Unless the hero or guru proves by the scientific method that their success will be replicated by any other who follows their ways, I know that I’ve got an inspirational story, but not a proven methodology for sure success. I do love a success story, but, as well as being a businessman, I’m an engineer and a scientist, and I need proof that a wonderful outcome was not by luck, or by accident. One lone data point is not trustworthy evidence—no matter who wrote the book.
When you want to make a change in your life, or a change in a business, you too will do what we all do: go to the guru and the hero. We look at their story and think that because they had success you too can have success. But another person’s, or another company’s, impressive result is only a sample size of one—it is not yet believable proof that they weren’t just very lucky, or they made a fortunate mistake.
Run Your Own Experiments When You Have a Sample Size of One and Replicate It Many Times
It’s wise that you do your own experiments to check that a hero’s guidance also works for you. Use the scientific method in low cost trials to test their claim. If after doing a fair and valid test, you see improvement, then let other people do more trials so you have a string of sequential, independent successes. Luck and fortunate mistakes can still give you those results, but now your excitement seems to have valid justification. If there is no clear improvement from the test, then take the view that the hero’s success was a lone data point that luckily happened to them, but it is now unrepeatable.
If you act on what gurus and heroes say to do, without independent proofs of veracity, you’ll be hoping for success. If you go ahead anyway on the hunch, and you are successful… thank your lucky stars that the chocolate wheel stopped on your number.
All the very best to you,
Lifetime Reliability Solutions HQ